def irma_percen(irma_tc_s, irma_tc_n, exp_s, exp_n):
""" Plot irma damage in % in lesser antilles and TCA. """
if_exp = ImpactFuncSet()
if_em = IFTropCyclone()
if_em.set_emanuel_usa()
if_exp.add_func(if_em)
fig, axs = plt.subplots(1,
2,
figsize=(16, 20),
subplot_kw=dict(projection=ccrs.PlateCarree()),
squeeze=True,
sharex=False,
sharey=False)
for idx, axis in enumerate(axs.flatten()):
grid = axis.gridlines(draw_labels=True, alpha=0.2)
grid.xlabels_top = grid.ylabels_right = False
grid.xformatter = LONGITUDE_FORMATTER
grid.yformatter = LATITUDE_FORMATTER
# south
plot_percen(irma_tc_s, exp_s, if_exp, axs[0])
# nord
im = plot_percen(irma_tc_n, exp_n, if_exp, axs[1])
plt.subplots_adjust(wspace=0.14)
fig.subplots_adjust(right=0.88)
cbar_ax = fig.add_axes([0.885, 0.4285, 0.03, 0.148])
fig.colorbar(im, cax=cbar_ax, orientation='vertical', label='% Damage')
return fig
def calc_imp(expo_dict, tc_dict, data_dir):
""" Compute impacts of TCs in every island group. """
try:
abs_path = os.path.join(data_dir, 'imp_isl.p')
with open(abs_path, 'rb') as f:
imp_dict = pickle.load(f)
print('Loaded imp_isl:', len(imp_dict))
except FileNotFoundError:
if_exp = ImpactFuncSet()
if_em = IFTropCyclone()
if_em.set_emanuel_usa()
if_exp.add_func(if_em)
imp_dict = dict()
for isl_iso in expo_dict:
imp = Impact()
imp.calc(expo_dict[isl_iso], if_exp, tc_dict[isl_iso])
imp_dict[isl_iso] = imp
save(os.path.join(data_dir, 'imp_isl.p'), imp_dict)
return imp_dict
def plot_right(irma_tc, exp, ax, scale_pos, plot_line=False):
""" Plot irma damage in USD. """
if_exp = ImpactFuncSet()
if_em = IFTropCyclone()
if_em.set_emanuel_usa()
if_exp.add_func(if_em)
imp_irma = Impact()
imp_irma.calc(exp, if_exp, irma_tc)
extent = [
exp.longitude.min() - BUFFER_DEG,
exp.longitude.max() + BUFFER_DEG,
exp.latitude.min() - BUFFER_DEG,
exp.latitude.max() + BUFFER_DEG
]
ax.set_extent((extent))
u_plot.add_shapes(ax)
sel_pos = np.argwhere(imp_irma.eai_exp > 0)[:, 0]
hex_bin = ax.hexbin(imp_irma.coord_exp[sel_pos, 1],
imp_irma.coord_exp[sel_pos, 0],
C=imp_irma.eai_exp[sel_pos],
reduce_C_function=np.average,
transform=ccrs.PlateCarree(),
gridsize=2000,
norm=LogNorm(vmin=MIN_VAL, vmax=MAX_VAL),
cmap='YlOrRd',
vmin=MIN_VAL,
vmax=MAX_VAL)
ax.set_title('')
ax.grid(False)
add_cntry_names(ax, extent)
scale_bar(ax, scale_pos, 10)
if plot_line:
x1, y1 = [-64.57, -64.82], [18.28, 18.47]
ax.plot(x1, y1, linewidth=1.0, color='grey', linestyle='--')
return hex_bin